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Portrait Ruben Carballo de Cal
von Ruben Carballo de la Cal
Cloud Engineer, aus Basel

#knowledgesharing #level 100

How does data replication work??

Monday morning is 3 a.m., the phone rings... a disaster has impacted a data center, all the data is gone, and business resumes in four hours... That’s exactly why you need a remote physical location for data replication.
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With Nutanix Data Protection you can protect/replicate everything that is running in a Nutanix cluster, whether it is a VM, a Volume Group (only supported by Prism Element replication), or a File Share.

Depending on your business requirements, Nutanix can help you achieve this using multiple "flavors" (asynchronous or synchronous) that are available.

  • Asynchronous replication
    • Hypervisor agnostic
    • Delay replication time 1h
  • Near Sync
    • Asynchronous replication from 1 min up to 15 mins
    • Hypervisor agnostic
    • Support only one to one replication
    • Different technology used for Near Sync: Lightweight Snapshots (LWS).
  • Synchronous replication – Metro availability
    • Hypervisor agnostic
    • Metro cluster configuration for VMWare
    • 0ms replication delay
    • Possible to automate failover using a Witness VM for ESXi and Prism Central for AHV
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Nutanix's data protection is very granular and flexible at the topology level, and it allows you to configure different scenarios:

  • Two-Way Mirroring (aka one to one)
    That’s the most common protection strategy and consists of mirroring the infrastructure from site A to site B. It’s possible to configure a protection domain A (from A to B) and protection domain B (from B to A) to make both sites act active-passive, spread the workload, and avoid an outage on all the VMs as in case of issues, only 50% of the VMs would be affected and the rest runs intact.
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  • One to Many
    In this replication scenario, A is the main location there are multiple remote locations. The main workload is running on-site A and sites B and C (remote locations) act as backup for specific workloads.
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  • Many to One
    Imagine there are multiple branch offices, and all the data is backed up to a main central location. This is a classical example of ROBO data protection architecture where all the workload running on ROBO clusters is backed up to a main big cluster.
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  • Many to Many
    That topology allows the most flexible setup. Using it you ensure the best application continuity and protection strategy.
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  • Cloud as recovery site – Xi Leap

Nutanix offers the possibility to use its integrated cloud solution as a recovery site, Xi Leap. Xi Leap eliminates the need for a dedicated Disaster Recovery Site, and It’s managed by Prism Central. There are a few points to focus on:

  • Availability Zones
    • All Nutanix clusters connected to a Prism Central instance or Xi Leap Zone. Depending on the architecture, it can represent a DataCenter, server room, or geographic territory.
  • Protection Policies
    • Define the RPO (Recovery Point Objective), retention period.
  • Categories
    • Used to assign VMs to protection policies.
  • Recovery Plans
    • Englobe the specifications of the disaster recovery plan like VMs boot order, IP address management, and virtual networking mappings.

Xi Leap availability zones over the world:

  • US West
  • US East
  • UK
  • Germany
  • Italy
  • Japan

Xi Leap is “cross hypervisor” DR (from ESXi to AHV), minimum RPO is 1h, allows the customer to save money, rack space, cooling power, network switches ports as a secondary infrastructure, which is not used often, is not in place.

 

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Conclusion

Nutanix data protection allows multiple topologies and replication setup choices to fit 100% of your business requirements. It is possible to combine all the options and create complex recovery scenarios to guarantee data persistence and availability.  

Even is possible to configure the Cloud as a recovery site… Nutanix is cloud-friendly!!

 

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Vollautomatisierte MLOps-Pipeline - Teil 1

Im vorigen Blogbeitrag haben wir die Architektur und die Demo einer Pipeline für die Dateneingabe in Amazon SageMaker Feature Store in nahezu Echtzeit vorgestellt. In diesem und dem folgenden Beitrag werden wir die vollständig automatisierte MLOps-Pipeline vorstellen.
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Nahezu Echtzeit-Dateneingabe in den SageMaker Feature Store

Dieser Blog-Beitrag ist der erste Teil einer dreiteiligen Serie über das Testen einer vollautomatischen MLOps-Pipeline für Machine-Learning-Vorhersagen auf Zeitreihendaten in AWS, die nahezu in Echtzeit vorliegen. In diesem ersten Teil konzentrieren wir uns auf die Dateneingabe-Pipeline in den Amazon SageMaker Feature Store.
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AWS AppConfig for Serverless Applications Demo

Wäre es nicht schön, wenn die Applikationskonfiguration von der Infrastrukturkonfiguration und dem Code entkoppelt werden könnte? An dieser Stelle kann AWS AppConfig (eine Komponente von AWS Systems Manager) helfen (Artikel in Englisch)
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Baue eine Cloud-native Plattform für Deine Kunden

Was hat die Geschäftsidee eines Hotels mit dem Plattformansatz in der Cloud Native Welt gemeinsam? Und wie kannst Du den Anforderungen Deiner Kunden gerecht werden? Erfahre mehr darüber in diesem Blogbeitrag.
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